Affective video content analysis has emerged as one of the most challenging and essential
research tasks as it aims to analyze the emotions elicited by videos automatically. However …

This paper proposes a framework for training language-invariant cross-modal retrieval
models. We also introduce a novel character-based word-embedding approach, allowing …

Multi-label text classification (MLTC) is a technique to categorize texts into more than a
single category and used extensively in various real-life problems. Such classifications …

As the scale of the film industry grows, the demand for well-established movie databases is
also growing. The genre of a movie supplies information on its overall content and has …

Movies were still a very popular means of entertainment. The current distribution of internet
users causes a large amount of movie data to be created and distributed online. The …

In this paper, we present the framework, SEMPD (the Semantic Extraction of Movie poster
based on fundamental of poster Design) for multi-label genre classification in the state of …

Movie posters are not just decorative; they are meticulously designed to capture the essence
of a movie, such as its genre, storyline, and tone/vibe. For decades, movie posters have …

In the film industry, movie posters have been an essential part of advertising and marketing
for many decades and continue to play a vital role even today in the form of digital posters …

Genre-based movie classification is a significant topic in text processing and machine
learning. An automatic system that classifies movies by genre can help people find their top …

A movie poster image is one of the important media in the filmmaking process, providing
valuable information about the movie, such as movie titles, characters, and genres …